AI Developer — RAG based AI agent for data-driven chatbots (Current)
Developed and contributed to a Retrieval-Augmented Generation (RAG) based AI agent intended for building intelligent, data-driven chatbots. Implemented a plug-and-play chatbot framework that supports injecting knowledge from heterogeneous sources such as documents, URLs, and databases. Focused on enabling context-aware responses by integrating retrieval pipelines with LLM prompting logic. • Built RAG ingestion flows for documents/URLs/database sources. • Designed a modular framework to minimize configuration effort for users. • Worked on embedding/indexing concepts to support context retrieval. • Integrated the agent behavior around prompt engineering for realistic chatbot use.